InnoMat.AI provides an on‑premise AI inspection platform that runs edge‑optimized deep‑learning models to detect equipment anomalies in real time across visual, infrared, and ultrasonic data. The solution integrates with SCADA, MES, and ERP systems via standard APIs and includes workflow automation and mechanical simulation for predictive maintenance, all within secure, air‑gapped environments.
Funding
Funding not disclosed
Founders
Product
Problem
Many industrial facilities rely on manual visual inspections or cloud‑based AI tools that cannot be used in secure, air‑gapped environments. This limits the speed and consistency of defect detection, increases equipment downtime, and raises compliance concerns for sectors such as energy, manufacturing, and oil & gas.
Solution
InnoMat.AI delivers an enterprise‑grade, on‑premise AI inspection platform that runs entirely within a facility’s secure network. The system uses edge‑optimized deep‑learning models to identify equipment anomalies in real time, eliminating the latency and data‑privacy issues of cloud solutions. Integrated workflow management software automates inspection scheduling, result logging, and corrective‑action tracking, boosting operational efficiency. A built‑in mechanical behavior simulation module predicts stress and wear patterns, enabling proactive maintenance planning. The platform is fully customizable and can be integrated with existing SCADA, MES, or ERP systems via standard APIs, ensuring seamless adoption across legacy infrastructures. Dedicated support and training resources help engineering teams maximize the technology’s value without extensive AI expertise.
Target Audience
The primary customers are engineering, quality‑assurance, and maintenance teams in high‑security industrial sectors such as energy plants, manufacturing facilities, and oil & gas operations that require reliable, on‑site defect detection and predictive maintenance capabilities.
Features
- Edge‑deployed AI inference engine with GPU acceleration for sub‑second defect detection on high‑resolution sensor data
- Deep‑learning models trained on industry‑specific defect datasets, supporting multi‑modal inputs (visual, infrared, ultrasonic)
- Integrated inspection workflow dashboard that automates task assignment, result validation, and audit‑trail generation
- Mechanical behavior simulation using finite‑element analysis to forecast wear, fatigue, and failure modes
- Secure data handling with AES‑256 encryption, role‑based access control, and on‑site data storage to meet compliance requirements
- RESTful and OPC‑UA APIs for seamless integration with SCADA, MES, ERP, and digital twin platforms
- Modular architecture allowing custom model training, rule‑based alerts, and UI branding to fit unique operational needs
- 24/7 expert support and on‑site training programs to accelerate deployment and user adoption